Add EEGViT config

config.json

@@ -1,25 +1,38 @@
 {
-  "architectures": [
-    "EEGViTAutoModel"
-  ],
-  "attention_probs_dropout_prob": 0.0,
+  "attention_probs_dropout_prob": 0.1,
   "auto_map": {
-    "AutoModel": "eegvit_model.EEGViTAutoModel"
+    "AutoConfig": "configuration_eegvit.EEGViTConfig"
   },
-  "encoder_stride": 16,
-  "hidden_act": "gelu",
-  "hidden_dropout_prob": 0.0,
+  "classifier_dropout": 0.1,
+  "conv1_kernel_size": [
+    1,
+    36
+  ],
+  "conv1_out_channels": 256,
+  "conv1_padding": [
+    0,
+    2
+  ],
+  "conv1_stride": [
+    1,
+    36
+  ],
+  "hidden_dropout_prob": 0.1,
   "hidden_size": 768,
-  "image_size": 224,
+  "image_size": [
+    129,
+    14
+  ],
   "initializer_range": 0.02,
   "intermediate_size": 3072,
   "layer_norm_eps": 1e-12,
-  "model_type": "vit",
+  "model_type": "eegvit",
   "num_attention_heads": 12,
-  "num_channels": 3,
+  "num_channels": 256,
   "num_hidden_layers": 12,
-  "patch_size": 16,
-  "qkv_bias": true,
-  "torch_dtype": "float32",
+  "patch_size": [
+    8,
+    1
+  ],
   "transformers_version": "4.46.1"
 }

configuration_eegvit.py

@@ -0,0 +1,50 @@
+from transformers import PretrainedConfig
+
+class EEGViTConfig(PretrainedConfig):
+    model_type = "eegvit"
+
+    def __init__(
+        self,
+        conv1_out_channels=256,
+        conv1_kernel_size=(1, 36),
+        conv1_stride=(1, 36),
+        conv1_padding=(0, 2),
+        num_channels=256,
+        image_size=(129, 14),
+        patch_size=(8, 1),
+        hidden_size=768,
+        num_hidden_layers=12,
+        num_attention_heads=12,
+        intermediate_size=3072,
+        hidden_dropout_prob=0.1,
+        attention_probs_dropout_prob=0.1,
+        initializer_range=0.02,
+        layer_norm_eps=1e-12,
+        classifier_dropout=0.1,
+        num_labels=2,
+        **kwargs
+    ):
+        super().__init__(**kwargs)
+        
+        # Conv1 settings
+        self.conv1_out_channels = conv1_out_channels
+        self.conv1_kernel_size = conv1_kernel_size
+        self.conv1_stride = conv1_stride
+        self.conv1_padding = conv1_padding
+        
+        # ViT specific settings
+        self.num_channels = num_channels
+        self.image_size = image_size
+        self.patch_size = patch_size
+        self.hidden_size = hidden_size
+        self.num_hidden_layers = num_hidden_layers
+        self.num_attention_heads = num_attention_heads
+        self.intermediate_size = intermediate_size
+        self.hidden_dropout_prob = hidden_dropout_prob
+        self.attention_probs_dropout_prob = attention_probs_dropout_prob
+        self.initializer_range = initializer_range
+        self.layer_norm_eps = layer_norm_eps
+        
+        # Classifier settings
+        self.classifier_dropout = classifier_dropout
+        self.num_labels = num_labels